AI RESEARCH
FBCIR: Balancing Cross-Modal Focuses in Composed Image Retrieval
arXiv CS.AI
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ArXi:2603.11520v1 Announce Type: cross Composed image retrieval (CIR) requires multi-modal models to jointly reason over visual content and semantic modifications presented in text-image input pairs. While current CIR models achieve strong performance on common benchmark cases, their accuracies often degrades in challenging scenarios where negative candidates are semantically aligned with the query image or text. In this paper, we attribute this degradation to focus imbalances, where models disproportionately attend to one modality while neglecting the other.